1 | from asap.scantable import scantable
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2 | from asap import rcParams
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3 | from asap import print_log
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4 | from asap import selector
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5 | from asap import asaplog
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6 | from asap import asaplotgui
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7 |
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8 | def average_time(*args, **kwargs):
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9 | """
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10 | Return the (time) average of a scan or list of scans. [in channels only]
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11 | The cursor of the output scan is set to 0
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12 | Parameters:
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13 | one scan or comma separated scans or a list of scans
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14 | mask: an optional mask (only used for 'var' and 'tsys' weighting)
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15 | scanav: True averages each scan separately.
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16 | False (default) averages all scans together,
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17 | weight: Weighting scheme.
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18 | 'none' (mean no weight)
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19 | 'var' (1/var(spec) weighted)
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20 | 'tsys' (1/Tsys**2 weighted)
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21 | 'tint' (integration time weighted)
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22 | 'tintsys' (Tint/Tsys**2)
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23 | 'median' ( median averaging)
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24 | align: align the spectra in velocity before averaging. It takes
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25 | the time of the first spectrum in the first scantable
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26 | as reference time.
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27 | Example:
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28 | # return a time averaged scan from scana and scanb
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29 | # without using a mask
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30 | scanav = average_time(scana,scanb)
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31 | # or equivalent
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32 | # scanav = average_time([scana, scanb])
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33 | # return the (time) averaged scan, i.e. the average of
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34 | # all correlator cycles
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35 | scanav = average_time(scan, scanav=True)
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36 | """
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37 | scanav = False
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38 | if kwargs.has_key('scanav'):
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39 | scanav = kwargs.get('scanav')
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40 | weight = 'tint'
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41 | if kwargs.has_key('weight'):
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42 | weight = kwargs.get('weight')
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43 | mask = ()
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44 | if kwargs.has_key('mask'):
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45 | mask = kwargs.get('mask')
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46 | align = False
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47 | if kwargs.has_key('align'):
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48 | align = kwargs.get('align')
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49 | compel = False
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50 | if kwargs.has_key('compel'):
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51 | compel = kwargs.get('compel')
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52 | varlist = vars()
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53 | if isinstance(args[0],list):
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54 | lst = args[0]
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55 | elif isinstance(args[0],tuple):
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56 | lst = list(args[0])
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57 | else:
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58 | lst = list(args)
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59 |
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60 | del varlist["kwargs"]
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61 | varlist["args"] = "%d scantables" % len(lst)
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62 | # need special formatting here for history...
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63 |
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64 | from asap._asap import stmath
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65 | stm = stmath()
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66 | for s in lst:
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67 | if not isinstance(s,scantable):
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68 | msg = "Please give a list of scantables"
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69 | if rcParams['verbose']:
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70 | #print msg
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71 | asaplog.push(msg)
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72 | print_log('ERROR')
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73 | return
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74 | else:
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75 | raise TypeError(msg)
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76 | if scanav: scanav = "SCAN"
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77 | else: scanav = "NONE"
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78 | alignedlst = []
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79 | if align:
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80 | refepoch = lst[0].get_time(0)
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81 | for scan in lst:
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82 | alignedlst.append(scan.freq_align(refepoch,insitu=False))
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83 | else:
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84 | alignedlst = lst
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85 | if weight.upper() == 'MEDIAN':
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86 | # median doesn't support list of scantables - merge first
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87 | merged = None
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88 | if len(alignedlst) > 1:
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89 | merged = merge(alignedlst)
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90 | else:
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91 | merged = alignedlst[0]
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92 | s = scantable(stm._averagechannel(merged, 'MEDIAN', scanav))
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93 | del merged
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94 | else:
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95 | #s = scantable(stm._average(alignedlst, mask, weight.upper(), scanav))
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96 | s = scantable(stm._new_average(alignedlst, compel, mask, weight.upper(), scanav))
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97 | s._add_history("average_time",varlist)
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98 | print_log()
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99 | return s
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100 |
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101 | def quotient(source, reference, preserve=True):
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102 | """
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103 | Return the quotient of a 'source' (signal) scan and a 'reference' scan.
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104 | The reference can have just one scan, even if the signal has many. Otherwise
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105 | they must have the same number of scans.
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106 | The cursor of the output scan is set to 0
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107 | Parameters:
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108 | source: the 'on' scan
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109 | reference: the 'off' scan
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110 | preserve: you can preserve (default) the continuum or
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111 | remove it. The equations used are
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112 | preserve: Output = Toff * (on/off) - Toff
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113 | remove: Output = Toff * (on/off) - Ton
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114 | """
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115 | varlist = vars()
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116 | from asap._asap import stmath
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117 | stm = stmath()
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118 | stm._setinsitu(False)
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119 | s = scantable(stm._quotient(source, reference, preserve))
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120 | s._add_history("quotient",varlist)
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121 | print_log()
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122 | return s
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123 |
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124 | def dototalpower(calon, caloff, tcalval=0.0):
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125 | """
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126 | Do calibration for CAL on,off signals.
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127 | Adopted from GBTIDL dototalpower
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128 | Parameters:
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129 | calon: the 'cal on' subintegration
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130 | caloff: the 'cal off' subintegration
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131 | tcalval: user supplied Tcal value
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132 | """
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133 | varlist = vars()
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134 | from asap._asap import stmath
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135 | stm = stmath()
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136 | stm._setinsitu(False)
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137 | s = scantable(stm._dototalpower(calon, caloff, tcalval))
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138 | s._add_history("dototalpower",varlist)
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139 | print_log()
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140 | return s
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141 |
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142 | def dosigref(sig, ref, smooth, tsysval=0.0, tauval=0.0):
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143 | """
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144 | Calculate a quotient (sig-ref/ref * Tsys)
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145 | Adopted from GBTIDL dosigref
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146 | Parameters:
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147 | sig: on source data
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148 | ref: reference data
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149 | smooth: width of box car smoothing for reference
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150 | tsysval: user specified Tsys (scalar only)
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151 | tauval: user specified Tau (required if tsysval is set)
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152 | """
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153 | varlist = vars()
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154 | from asap._asap import stmath
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155 | stm = stmath()
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156 | stm._setinsitu(False)
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157 | s = scantable(stm._dosigref(sig, ref, smooth, tsysval, tauval))
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158 | s._add_history("dosigref",varlist)
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159 | print_log()
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160 | return s
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161 |
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162 | def calps(scantab, scannos, smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False):
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163 | """
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164 | Calibrate GBT position switched data
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165 | Adopted from GBTIDL getps
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166 | Currently calps identify the scans as position switched data if they
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167 | contain '_ps' in the source name. The data must contains 'CAL' signal
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168 | on/off in each integration. To identify 'CAL' on state, the word, 'calon'
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169 | need to be present in the source name field.
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170 | (GBT MS data reading process to scantable automatically append these
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171 | id names to the source names)
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172 |
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173 | Parameters:
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174 | scantab: scantable
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175 | scannos: list of scan numbers
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176 | smooth: optional box smoothing order for the reference
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177 | (default is 1 = no smoothing)
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178 | tsysval: optional user specified Tsys (default is 0.0,
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179 | use Tsys in the data)
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180 | tauval: optional user specified Tau
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181 | tcalval: optional user specified Tcal (default is 0.0,
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182 | use Tcal value in the data)
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183 | """
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184 | varlist = vars()
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185 | # check for the appropriate data
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186 | s = scantab.get_scan('*_ps*')
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187 | if s is None:
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188 | msg = "The input data appear to contain no position-switch mode data."
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189 | if rcParams['verbose']:
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190 | #print msg
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191 | asaplog.push(msg)
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192 | print_log('ERROR')
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193 | return
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194 | else:
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195 | raise TypeError(msg)
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196 | ssub = s.get_scan(scannos)
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197 | if ssub is None:
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198 | msg = "No data was found with given scan numbers!"
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199 | if rcParams['verbose']:
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200 | #print msg
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201 | asaplog.push(msg)
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202 | print_log('ERROR')
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203 | return
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204 | else:
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205 | raise TypeError(msg)
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206 | ssubon = ssub.get_scan('*calon')
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207 | ssuboff = ssub.get_scan('*[^calon]')
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208 | if ssubon.nrow() != ssuboff.nrow():
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209 | msg = "mismatch in numbers of CAL on/off scans. Cannot calibrate. Check the scan numbers."
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210 | if rcParams['verbose']:
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211 | #print msg
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212 | asaplog.push(msg)
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213 | print_log('ERROR')
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214 | return
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215 | else:
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216 | raise TypeError(msg)
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217 | cals = dototalpower(ssubon, ssuboff, tcalval)
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218 | sig = cals.get_scan('*ps')
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219 | ref = cals.get_scan('*psr')
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220 | if sig.nscan() != ref.nscan():
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221 | msg = "mismatch in numbers of on/off scans. Cannot calibrate. Check the scan numbers."
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222 | if rcParams['verbose']:
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223 | #print msg
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224 | asaplog.push(msg)
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225 | print_log('ERROR')
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226 | return
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227 | else:
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228 | raise TypeError(msg)
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229 |
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230 | #for user supplied Tsys
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231 | if tsysval>0.0:
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232 | if tauval<=0.0:
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233 | msg = "Need to supply a valid tau to use the supplied Tsys"
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234 | if rcParams['verbose']:
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235 | #print msg
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236 | asaplog.push(msg)
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237 | print_log('ERROR')
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238 | return
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239 | else:
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240 | raise TypeError(msg)
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241 | else:
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242 | sig.recalc_azel()
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243 | ref.recalc_azel()
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244 | #msg = "Use of user specified Tsys is not fully implemented yet."
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245 | #if rcParams['verbose']:
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246 | # print msg
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247 | # return
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248 | #else:
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249 | # raise TypeError(msg)
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250 | # use get_elevation to get elevation and
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251 | # calculate a scaling factor using the formula
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252 | # -> tsys use to dosigref
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253 |
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254 | #ress = dosigref(sig, ref, smooth, tsysval)
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255 | ress = dosigref(sig, ref, smooth, tsysval, tauval)
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256 | ###
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257 | if verify:
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258 | # get data
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259 | import numpy
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260 | precal={}
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261 | postcal=[]
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262 | keys=['ps','ps_calon','psr','psr_calon']
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263 | ifnos=list(ssub.getifnos())
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264 | polnos=list(ssub.getpolnos())
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265 | sel=selector()
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266 | for i in range(2):
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267 | ss=ssuboff.get_scan('*'+keys[2*i])
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268 | ll=[]
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269 | for j in range(len(ifnos)):
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270 | for k in range(len(polnos)):
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271 | sel.set_ifs(ifnos[j])
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272 | sel.set_polarizations(polnos[k])
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273 | try:
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274 | ss.set_selection(sel)
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275 | except:
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276 | continue
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277 | ll.append(numpy.array(ss._getspectrum(0)))
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278 | sel.reset()
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279 | ss.set_selection()
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280 | precal[keys[2*i]]=ll
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281 | del ss
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282 | ss=ssubon.get_scan('*'+keys[2*i+1])
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283 | ll=[]
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284 | for j in range(len(ifnos)):
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285 | for k in range(len(polnos)):
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286 | sel.set_ifs(ifnos[j])
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287 | sel.set_polarizations(polnos[k])
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288 | try:
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289 | ss.set_selection(sel)
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290 | except:
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291 | continue
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292 | ll.append(numpy.array(ss._getspectrum(0)))
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293 | sel.reset()
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294 | ss.set_selection()
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295 | precal[keys[2*i+1]]=ll
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296 | del ss
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297 | for j in range(len(ifnos)):
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298 | for k in range(len(polnos)):
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299 | sel.set_ifs(ifnos[j])
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300 | sel.set_polarizations(polnos[k])
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301 | try:
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302 | ress.set_selection(sel)
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303 | except:
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304 | continue
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305 | postcal.append(numpy.array(ress._getspectrum(0)))
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306 | sel.reset()
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307 | ress.set_selection()
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308 | del sel
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309 | # plot
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310 | print_log()
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311 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.')
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312 | print_log('WARN')
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313 | p=asaplotgui.asaplotgui()
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314 | #nr=min(6,len(ifnos)*len(polnos))
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315 | nr=len(ifnos)*len(polnos)
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316 | titles=[]
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317 | btics=[]
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318 | if nr<4:
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319 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False)
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320 | for i in range(2*nr):
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321 | b=False
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322 | if i >= 2*nr-2:
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323 | b=True
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324 | btics.append(b)
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325 | elif nr==4:
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326 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False)
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327 | for i in range(2*nr):
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328 | b=False
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329 | if i >= 2*nr-4:
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330 | b=True
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331 | btics.append(b)
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332 | elif nr<7:
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333 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
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334 | for i in range(2*nr):
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335 | if i >= 2*nr-4:
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336 | b=True
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337 | btics.append(b)
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338 | else:
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339 | print_log()
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340 | asaplog.push('Only first 6 [if,pol] pairs are plotted.')
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341 | print_log('WARN')
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342 | nr=6
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343 | for i in range(2*nr):
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344 | b=False
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345 | if i >= 2*nr-4:
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346 | b=True
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347 | btics.append(b)
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348 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
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349 | for i in range(nr):
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350 | p.subplot(2*i)
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351 | p.color=0
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352 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
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353 | titles.append(title)
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354 | #p.set_axes('title',title,fontsize=40)
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355 | ymin=1.0e100
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356 | ymax=-1.0e100
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357 | nchan=s.nchan()
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358 | edge=int(nchan*0.01)
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359 | for j in range(4):
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360 | spmin=min(precal[keys[j]][i][edge:nchan-edge])
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361 | spmax=max(precal[keys[j]][i][edge:nchan-edge])
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362 | ymin=min(ymin,spmin)
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363 | ymax=max(ymax,spmax)
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364 | for j in range(4):
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365 | if i==0:
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366 | p.set_line(label=keys[j])
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367 | else:
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368 | p.legend()
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369 | p.plot(precal[keys[j]][i])
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370 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
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371 | if not btics[2*i]:
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372 | p.axes.set_xticks([])
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373 | p.subplot(2*i+1)
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374 | p.color=0
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375 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
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376 | titles.append(title)
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377 | #p.set_axes('title',title)
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378 | p.legend()
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379 | ymin=postcal[i][edge:nchan-edge].min()
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380 | ymax=postcal[i][edge:nchan-edge].max()
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381 | p.plot(postcal[i])
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382 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
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383 | if not btics[2*i+1]:
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384 | p.axes.set_xticks([])
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385 | for i in range(2*nr):
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386 | p.subplot(i)
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387 | p.set_axes('title',titles[i],fontsize='medium')
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388 | x=raw_input('Accept calibration ([y]/n): ' )
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389 | if x.upper() == 'N':
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390 | p.unmap()
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391 | del p
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392 | return scabtab
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393 | p.unmap()
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394 | del p
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395 | ###
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396 | ress._add_history("calps", varlist)
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397 | print_log()
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398 | return ress
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399 |
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400 | def calnod(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False):
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401 | """
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402 | Do full (but a pair of scans at time) processing of GBT Nod data
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403 | calibration.
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404 | Adopted from GBTIDL's getnod
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405 | Parameters:
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406 | scantab: scantable
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407 | scannos: a pair of scan numbers, or the first scan number of the pair
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408 | smooth: box car smoothing order
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409 | tsysval: optional user specified Tsys value
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410 | tauval: optional user specified tau value (not implemented yet)
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411 | tcalval: optional user specified Tcal value
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412 | """
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413 | varlist = vars()
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414 | from asap._asap import stmath
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415 | stm = stmath()
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416 | stm._setinsitu(False)
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417 |
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418 | # check for the appropriate data
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419 | s = scantab.get_scan('*_nod*')
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420 | if s is None:
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421 | msg = "The input data appear to contain no Nod observing mode data."
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422 | if rcParams['verbose']:
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423 | #print msg
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424 | asaplog.push(msg)
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425 | print_log('ERROR')
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426 | return
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427 | else:
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428 | raise TypeError(msg)
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429 |
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430 | # need check correspondance of each beam with sig-ref ...
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431 | # check for timestamps, scan numbers, subscan id (not available in
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432 | # ASAP data format...). Assume 1st scan of the pair (beam 0 - sig
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433 | # and beam 1 - ref...)
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434 | # First scan number of paired scans or list of pairs of
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435 | # scan numbers (has to have even number of pairs.)
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436 |
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437 | #data splitting
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438 | scan1no = scan2no = 0
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439 |
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440 | if len(scannos)==1:
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441 | scan1no = scannos[0]
|
---|
442 | scan2no = scannos[0]+1
|
---|
443 | pairScans = [scan1no, scan2no]
|
---|
444 | else:
|
---|
445 | #if len(scannos)>2:
|
---|
446 | # msg = "calnod can only process a pair of nod scans at time."
|
---|
447 | # if rcParams['verbose']:
|
---|
448 | # print msg
|
---|
449 | # return
|
---|
450 | # else:
|
---|
451 | # raise TypeError(msg)
|
---|
452 | #
|
---|
453 | #if len(scannos)==2:
|
---|
454 | # scan1no = scannos[0]
|
---|
455 | # scan2no = scannos[1]
|
---|
456 | pairScans = list(scannos)
|
---|
457 |
|
---|
458 | if tsysval>0.0:
|
---|
459 | if tauval<=0.0:
|
---|
460 | msg = "Need to supply a valid tau to use the supplied Tsys"
|
---|
461 | if rcParams['verbose']:
|
---|
462 | #print msg
|
---|
463 | asaplog.push(msg)
|
---|
464 | print_log('ERROR')
|
---|
465 | return
|
---|
466 | else:
|
---|
467 | raise TypeError(msg)
|
---|
468 | else:
|
---|
469 | scantab.recalc_azel()
|
---|
470 | resspec = scantable(stm._donod(scantab, pairScans, smooth, tsysval,tauval,tcalval))
|
---|
471 | ###
|
---|
472 | if verify:
|
---|
473 | # get data
|
---|
474 | import numpy
|
---|
475 | precal={}
|
---|
476 | postcal=[]
|
---|
477 | keys=['nod','nod_calon']
|
---|
478 | ifnos=list(scantab.getifnos())
|
---|
479 | polnos=list(scantab.getpolnos())
|
---|
480 | sel=selector()
|
---|
481 | for i in range(2):
|
---|
482 | ss=scantab.get_scan('*'+keys[i])
|
---|
483 | ll=[]
|
---|
484 | ll2=[]
|
---|
485 | for j in range(len(ifnos)):
|
---|
486 | for k in range(len(polnos)):
|
---|
487 | sel.set_ifs(ifnos[j])
|
---|
488 | sel.set_polarizations(polnos[k])
|
---|
489 | sel.set_scans(pairScans[0])
|
---|
490 | try:
|
---|
491 | ss.set_selection(sel)
|
---|
492 | except:
|
---|
493 | continue
|
---|
494 | ll.append(numpy.array(ss._getspectrum(0)))
|
---|
495 | sel.reset()
|
---|
496 | ss.set_selection()
|
---|
497 | sel.set_ifs(ifnos[j])
|
---|
498 | sel.set_polarizations(polnos[k])
|
---|
499 | sel.set_scans(pairScans[1])
|
---|
500 | try:
|
---|
501 | ss.set_selection(sel)
|
---|
502 | except:
|
---|
503 | ll.pop()
|
---|
504 | continue
|
---|
505 | ll2.append(numpy.array(ss._getspectrum(0)))
|
---|
506 | sel.reset()
|
---|
507 | ss.set_selection()
|
---|
508 | key='%s%s' %(pairScans[0],keys[i].lstrip('nod'))
|
---|
509 | precal[key]=ll
|
---|
510 | key='%s%s' %(pairScans[1],keys[i].lstrip('nod'))
|
---|
511 | precal[key]=ll2
|
---|
512 | del ss
|
---|
513 | keys=precal.keys()
|
---|
514 | for j in range(len(ifnos)):
|
---|
515 | for k in range(len(polnos)):
|
---|
516 | sel.set_ifs(ifnos[j])
|
---|
517 | sel.set_polarizations(polnos[k])
|
---|
518 | sel.set_scans(pairScans[0])
|
---|
519 | try:
|
---|
520 | resspec.set_selection(sel)
|
---|
521 | except:
|
---|
522 | continue
|
---|
523 | postcal.append(numpy.array(resspec._getspectrum(0)))
|
---|
524 | sel.reset()
|
---|
525 | resspec.set_selection()
|
---|
526 | del sel
|
---|
527 | # plot
|
---|
528 | print_log()
|
---|
529 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.')
|
---|
530 | print_log('WARN')
|
---|
531 | p=asaplotgui.asaplotgui()
|
---|
532 | #nr=min(6,len(ifnos)*len(polnos))
|
---|
533 | nr=len(ifnos)*len(polnos)
|
---|
534 | titles=[]
|
---|
535 | btics=[]
|
---|
536 | if nr<4:
|
---|
537 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False)
|
---|
538 | for i in range(2*nr):
|
---|
539 | b=False
|
---|
540 | if i >= 2*nr-2:
|
---|
541 | b=True
|
---|
542 | btics.append(b)
|
---|
543 | elif nr==4:
|
---|
544 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False)
|
---|
545 | for i in range(2*nr):
|
---|
546 | b=False
|
---|
547 | if i >= 2*nr-4:
|
---|
548 | b=True
|
---|
549 | btics.append(b)
|
---|
550 | elif nr<7:
|
---|
551 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
|
---|
552 | for i in range(2*nr):
|
---|
553 | if i >= 2*nr-4:
|
---|
554 | b=True
|
---|
555 | btics.append(b)
|
---|
556 | else:
|
---|
557 | print_log()
|
---|
558 | asaplog.push('Only first 6 [if,pol] pairs are plotted.')
|
---|
559 | print_log('WARN')
|
---|
560 | nr=6
|
---|
561 | for i in range(2*nr):
|
---|
562 | b=False
|
---|
563 | if i >= 2*nr-4:
|
---|
564 | b=True
|
---|
565 | btics.append(b)
|
---|
566 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
|
---|
567 | for i in range(nr):
|
---|
568 | p.subplot(2*i)
|
---|
569 | p.color=0
|
---|
570 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
|
---|
571 | titles.append(title)
|
---|
572 | #p.set_axes('title',title,fontsize=40)
|
---|
573 | ymin=1.0e100
|
---|
574 | ymax=-1.0e100
|
---|
575 | nchan=scantab.nchan()
|
---|
576 | edge=int(nchan*0.01)
|
---|
577 | for j in range(4):
|
---|
578 | spmin=min(precal[keys[j]][i][edge:nchan-edge])
|
---|
579 | spmax=max(precal[keys[j]][i][edge:nchan-edge])
|
---|
580 | ymin=min(ymin,spmin)
|
---|
581 | ymax=max(ymax,spmax)
|
---|
582 | for j in range(4):
|
---|
583 | if i==0:
|
---|
584 | p.set_line(label=keys[j])
|
---|
585 | else:
|
---|
586 | p.legend()
|
---|
587 | p.plot(precal[keys[j]][i])
|
---|
588 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
---|
589 | if not btics[2*i]:
|
---|
590 | p.axes.set_xticks([])
|
---|
591 | p.subplot(2*i+1)
|
---|
592 | p.color=0
|
---|
593 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
|
---|
594 | titles.append(title)
|
---|
595 | #p.set_axes('title',title)
|
---|
596 | p.legend()
|
---|
597 | ymin=postcal[i][edge:nchan-edge].min()
|
---|
598 | ymax=postcal[i][edge:nchan-edge].max()
|
---|
599 | p.plot(postcal[i])
|
---|
600 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
---|
601 | if not btics[2*i+1]:
|
---|
602 | p.axes.set_xticks([])
|
---|
603 | for i in range(2*nr):
|
---|
604 | p.subplot(i)
|
---|
605 | p.set_axes('title',titles[i],fontsize='medium')
|
---|
606 | x=raw_input('Accept calibration ([y]/n): ' )
|
---|
607 | if x.upper() == 'N':
|
---|
608 | p.unmap()
|
---|
609 | del p
|
---|
610 | return scabtab
|
---|
611 | p.unmap()
|
---|
612 | del p
|
---|
613 | ###
|
---|
614 | resspec._add_history("calnod",varlist)
|
---|
615 | print_log()
|
---|
616 | return resspec
|
---|
617 |
|
---|
618 | def calfs(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False):
|
---|
619 | """
|
---|
620 | Calibrate GBT frequency switched data.
|
---|
621 | Adopted from GBTIDL getfs.
|
---|
622 | Currently calfs identify the scans as frequency switched data if they
|
---|
623 | contain '_fs' in the source name. The data must contains 'CAL' signal
|
---|
624 | on/off in each integration. To identify 'CAL' on state, the word, 'calon'
|
---|
625 | need to be present in the source name field.
|
---|
626 | (GBT MS data reading via scantable automatically append these
|
---|
627 | id names to the source names)
|
---|
628 |
|
---|
629 | Parameters:
|
---|
630 | scantab: scantable
|
---|
631 | scannos: list of scan numbers
|
---|
632 | smooth: optional box smoothing order for the reference
|
---|
633 | (default is 1 = no smoothing)
|
---|
634 | tsysval: optional user specified Tsys (default is 0.0,
|
---|
635 | use Tsys in the data)
|
---|
636 | tauval: optional user specified Tau
|
---|
637 | """
|
---|
638 | varlist = vars()
|
---|
639 | from asap._asap import stmath
|
---|
640 | stm = stmath()
|
---|
641 | stm._setinsitu(False)
|
---|
642 |
|
---|
643 | # check = scantab.get_scan('*_fs*')
|
---|
644 | # if check is None:
|
---|
645 | # msg = "The input data appear to contain no Nod observing mode data."
|
---|
646 | # if rcParams['verbose']:
|
---|
647 | # print msg
|
---|
648 | # return
|
---|
649 | # else:
|
---|
650 | # raise TypeError(msg)
|
---|
651 | s = scantab.get_scan(scannos)
|
---|
652 | del scantab
|
---|
653 |
|
---|
654 | resspec = scantable(stm._dofs(s, scannos, smooth, tsysval,tauval,tcalval))
|
---|
655 | ###
|
---|
656 | if verify:
|
---|
657 | # get data
|
---|
658 | ssub = s.get_scan(scannos)
|
---|
659 | ssubon = ssub.get_scan('*calon')
|
---|
660 | ssuboff = ssub.get_scan('*[^calon]')
|
---|
661 | import numpy
|
---|
662 | precal={}
|
---|
663 | postcal=[]
|
---|
664 | keys=['fs','fs_calon','fsr','fsr_calon']
|
---|
665 | ifnos=list(ssub.getifnos())
|
---|
666 | polnos=list(ssub.getpolnos())
|
---|
667 | sel=selector()
|
---|
668 | for i in range(2):
|
---|
669 | ss=ssuboff.get_scan('*'+keys[2*i])
|
---|
670 | ll=[]
|
---|
671 | for j in range(len(ifnos)):
|
---|
672 | for k in range(len(polnos)):
|
---|
673 | sel.set_ifs(ifnos[j])
|
---|
674 | sel.set_polarizations(polnos[k])
|
---|
675 | try:
|
---|
676 | ss.set_selection(sel)
|
---|
677 | except:
|
---|
678 | continue
|
---|
679 | ll.append(numpy.array(ss._getspectrum(0)))
|
---|
680 | sel.reset()
|
---|
681 | ss.set_selection()
|
---|
682 | precal[keys[2*i]]=ll
|
---|
683 | del ss
|
---|
684 | ss=ssubon.get_scan('*'+keys[2*i+1])
|
---|
685 | ll=[]
|
---|
686 | for j in range(len(ifnos)):
|
---|
687 | for k in range(len(polnos)):
|
---|
688 | sel.set_ifs(ifnos[j])
|
---|
689 | sel.set_polarizations(polnos[k])
|
---|
690 | try:
|
---|
691 | ss.set_selection(sel)
|
---|
692 | except:
|
---|
693 | continue
|
---|
694 | ll.append(numpy.array(ss._getspectrum(0)))
|
---|
695 | sel.reset()
|
---|
696 | ss.set_selection()
|
---|
697 | precal[keys[2*i+1]]=ll
|
---|
698 | del ss
|
---|
699 | sig=resspec.get_scan('*_fs')
|
---|
700 | ref=resspec.get_scan('*_fsr')
|
---|
701 | for k in range(len(polnos)):
|
---|
702 | for j in range(len(ifnos)):
|
---|
703 | sel.set_ifs(ifnos[j])
|
---|
704 | sel.set_polarizations(polnos[k])
|
---|
705 | try:
|
---|
706 | sig.set_selection(sel)
|
---|
707 | postcal.append(numpy.array(sig._getspectrum(0)))
|
---|
708 | except:
|
---|
709 | ref.set_selection(sel)
|
---|
710 | postcal.append(numpy.array(ref._getspectrum(0)))
|
---|
711 | sel.reset()
|
---|
712 | resspec.set_selection()
|
---|
713 | del sel
|
---|
714 | # plot
|
---|
715 | print_log()
|
---|
716 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.')
|
---|
717 | print_log('WARN')
|
---|
718 | p=asaplotgui.asaplotgui()
|
---|
719 | #nr=min(6,len(ifnos)*len(polnos))
|
---|
720 | nr=len(ifnos)/2*len(polnos)
|
---|
721 | titles=[]
|
---|
722 | btics=[]
|
---|
723 | if nr>3:
|
---|
724 | print_log()
|
---|
725 | asaplog.push('Only first 3 [if,pol] pairs are plotted.')
|
---|
726 | print_log('WARN')
|
---|
727 | nr=3
|
---|
728 | p.set_panels(rows=nr,cols=3,nplots=3*nr,ganged=False)
|
---|
729 | for i in range(3*nr):
|
---|
730 | b=False
|
---|
731 | if i >= 3*nr-3:
|
---|
732 | b=True
|
---|
733 | btics.append(b)
|
---|
734 | for i in range(nr):
|
---|
735 | p.subplot(3*i)
|
---|
736 | p.color=0
|
---|
737 | title='raw data IF%s,%s POL%s' % (ifnos[2*int(i/len(polnos))],ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)])
|
---|
738 | titles.append(title)
|
---|
739 | #p.set_axes('title',title,fontsize=40)
|
---|
740 | ymin=1.0e100
|
---|
741 | ymax=-1.0e100
|
---|
742 | nchan=s.nchan()
|
---|
743 | edge=int(nchan*0.01)
|
---|
744 | for j in range(4):
|
---|
745 | spmin=min(precal[keys[j]][i][edge:nchan-edge])
|
---|
746 | spmax=max(precal[keys[j]][i][edge:nchan-edge])
|
---|
747 | ymin=min(ymin,spmin)
|
---|
748 | ymax=max(ymax,spmax)
|
---|
749 | for j in range(4):
|
---|
750 | if i==0:
|
---|
751 | p.set_line(label=keys[j])
|
---|
752 | else:
|
---|
753 | p.legend()
|
---|
754 | p.plot(precal[keys[j]][i])
|
---|
755 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
---|
756 | if not btics[3*i]:
|
---|
757 | p.axes.set_xticks([])
|
---|
758 | p.subplot(3*i+1)
|
---|
759 | p.color=0
|
---|
760 | title='sig data IF%s POL%s' % (ifnos[2*int(i/len(polnos))],polnos[i%len(polnos)])
|
---|
761 | titles.append(title)
|
---|
762 | #p.set_axes('title',title)
|
---|
763 | p.legend()
|
---|
764 | ymin=postcal[2*i][edge:nchan-edge].min()
|
---|
765 | ymax=postcal[2*i][edge:nchan-edge].max()
|
---|
766 | p.plot(postcal[2*i])
|
---|
767 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
---|
768 | if not btics[3*i+1]:
|
---|
769 | p.axes.set_xticks([])
|
---|
770 | p.subplot(3*i+2)
|
---|
771 | p.color=0
|
---|
772 | title='ref data IF%s POL%s' % (ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)])
|
---|
773 | titles.append(title)
|
---|
774 | #p.set_axes('title',title)
|
---|
775 | p.legend()
|
---|
776 | ymin=postcal[2*i+1][edge:nchan-edge].min()
|
---|
777 | ymax=postcal[2*i+1][edge:nchan-edge].max()
|
---|
778 | p.plot(postcal[2*i+1])
|
---|
779 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
---|
780 | if not btics[3*i+2]:
|
---|
781 | p.axes.set_xticks([])
|
---|
782 | for i in range(3*nr):
|
---|
783 | p.subplot(i)
|
---|
784 | p.set_axes('title',titles[i],fontsize='medium')
|
---|
785 | x=raw_input('Accept calibration ([y]/n): ' )
|
---|
786 | if x.upper() == 'N':
|
---|
787 | p.unmap()
|
---|
788 | del p
|
---|
789 | return scabtab
|
---|
790 | p.unmap()
|
---|
791 | del p
|
---|
792 | ###
|
---|
793 | resspec._add_history("calfs",varlist)
|
---|
794 | print_log()
|
---|
795 | return resspec
|
---|
796 |
|
---|
797 | def simple_math(left, right, op='add', tsys=True):
|
---|
798 | """
|
---|
799 | Apply simple mathematical binary operations to two
|
---|
800 | scan tables, returning the result in a new scan table.
|
---|
801 | The operation is applied to both the correlations and the TSys data
|
---|
802 | The cursor of the output scan is set to 0
|
---|
803 | Parameters:
|
---|
804 | left: the 'left' scan
|
---|
805 | right: the 'right' scan
|
---|
806 | op: the operation: 'add' (default), 'sub', 'mul', 'div'
|
---|
807 | tsys: if True (default) then apply the operation to Tsys
|
---|
808 | as well as the data
|
---|
809 | """
|
---|
810 | #print "simple_math is deprecated use +=/* instead."
|
---|
811 | asaplog.push( "simple_math is deprecated use +=/* instead." )
|
---|
812 | print_log('WARN')
|
---|
813 |
|
---|
814 | def merge(*args):
|
---|
815 | """
|
---|
816 | Merge a list of scanatables, or comma-sperated scantables into one
|
---|
817 | scnatble.
|
---|
818 | Parameters:
|
---|
819 | A list [scan1, scan2] or scan1, scan2.
|
---|
820 | Example:
|
---|
821 | myscans = [scan1, scan2]
|
---|
822 | allscans = merge(myscans)
|
---|
823 | # or equivalent
|
---|
824 | sameallscans = merge(scan1, scan2)
|
---|
825 | """
|
---|
826 | varlist = vars()
|
---|
827 | if isinstance(args[0],list):
|
---|
828 | lst = tuple(args[0])
|
---|
829 | elif isinstance(args[0],tuple):
|
---|
830 | lst = args[0]
|
---|
831 | else:
|
---|
832 | lst = tuple(args)
|
---|
833 | varlist["args"] = "%d scantables" % len(lst)
|
---|
834 | # need special formatting her for history...
|
---|
835 | from asap._asap import stmath
|
---|
836 | stm = stmath()
|
---|
837 | for s in lst:
|
---|
838 | if not isinstance(s,scantable):
|
---|
839 | msg = "Please give a list of scantables"
|
---|
840 | if rcParams['verbose']:
|
---|
841 | #print msg
|
---|
842 | asaplog.push(msg)
|
---|
843 | print_log('ERROR')
|
---|
844 | return
|
---|
845 | else:
|
---|
846 | raise TypeError(msg)
|
---|
847 | s = scantable(stm._merge(lst))
|
---|
848 | s._add_history("merge", varlist)
|
---|
849 | print_log()
|
---|
850 | return s
|
---|
851 |
|
---|
852 | def calibrate( scantab, scannos=[], calmode='none', verify=None ):
|
---|
853 | """
|
---|
854 | Calibrate data.
|
---|
855 |
|
---|
856 | Parameters:
|
---|
857 | scantab: scantable
|
---|
858 | scannos: list of scan number
|
---|
859 | calmode: calibration mode
|
---|
860 | verify: verify calibration
|
---|
861 | """
|
---|
862 | antname = scantab.get_antennaname()
|
---|
863 | if ( calmode == 'nod' ):
|
---|
864 | asaplog.push( 'Calibrating nod data.' )
|
---|
865 | print_log()
|
---|
866 | scal = calnod( scantab, scannos=scannos, verify=verify )
|
---|
867 | elif ( calmode == 'quotient' ):
|
---|
868 | asaplog.push( 'Calibrating using quotient.' )
|
---|
869 | print_log()
|
---|
870 | scal = scantab.auto_quotient( verify=verify )
|
---|
871 | elif ( calmode == 'ps' ):
|
---|
872 | asaplog.push( 'Calibrating %s position-switched data.' % antname )
|
---|
873 | print_log()
|
---|
874 | if ( antname.find( 'APEX' ) != -1 ):
|
---|
875 | scal = apexcal( scantab, scannos, calmode, verify )
|
---|
876 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1 ):
|
---|
877 | scal = almacal( scantab, scannos, calmode, verify )
|
---|
878 | else:
|
---|
879 | scal = calps( scantab, scannos=scannos, verify=verify )
|
---|
880 | elif ( calmode == 'fs' or calmode == 'fsotf' ):
|
---|
881 | asaplog.push( 'Calibrating %s frequency-switched data.' % antname )
|
---|
882 | print_log()
|
---|
883 | if ( antname.find( 'APEX' ) != -1 ):
|
---|
884 | scal = apexcal( scantab, scannos, calmode, verify )
|
---|
885 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1 ):
|
---|
886 | scal = almacal( scantab, scannos, calmode, verify )
|
---|
887 | else:
|
---|
888 | scal = calfs( scantab, scannos=scannos, verify=verify )
|
---|
889 | elif ( calmode == 'otf' ):
|
---|
890 | asaplog.push( 'Calibrating %s On-The-Fly data.' % antname )
|
---|
891 | print_log()
|
---|
892 | scal = almacal( scantab, scannos, calmode, verify )
|
---|
893 | else:
|
---|
894 | asaplog.push( 'No calibration.' )
|
---|
895 | scal = scantab.copy()
|
---|
896 |
|
---|
897 | return scal
|
---|
898 |
|
---|
899 | def apexcal( scantab, scannos=[], calmode='none', verify=False ):
|
---|
900 | """
|
---|
901 | Calibrate APEX data
|
---|
902 |
|
---|
903 | Parameters:
|
---|
904 | scantab: scantable
|
---|
905 | scannos: list of scan number
|
---|
906 | calmode: calibration mode
|
---|
907 |
|
---|
908 | verify: verify calibration
|
---|
909 | """
|
---|
910 | from asap._asap import stmath
|
---|
911 | stm = stmath()
|
---|
912 | antname = scantab.get_antennaname()
|
---|
913 | ssub = scantab.get_scan( scannos )
|
---|
914 | scal = scantable( stm.cwcal( ssub, calmode, antname ) )
|
---|
915 | return scal
|
---|
916 |
|
---|
917 | def almacal( scantab, scannos=[], calmode='none', verify=False ):
|
---|
918 | """
|
---|
919 | Calibrate ALMA data
|
---|
920 |
|
---|
921 | Parameters:
|
---|
922 | scantab: scantable
|
---|
923 | scannos: list of scan number
|
---|
924 | calmode: calibration mode
|
---|
925 |
|
---|
926 | verify: verify calibration
|
---|
927 | """
|
---|
928 | from asap._asap import stmath
|
---|
929 | stm = stmath()
|
---|
930 | ssub = scantab.get_scan( scannos )
|
---|
931 | scal = scantable( stm.almacal( ssub, calmode ) )
|
---|
932 | return scal
|
---|
933 |
|
---|
934 | def splitant(filename, outprefix='',overwrite=False):
|
---|
935 | """
|
---|
936 | Split Measurement set by antenna name, save data as a scantables,
|
---|
937 | and return a list of filename.
|
---|
938 | Notice this method can only be available from CASA.
|
---|
939 | Prameter
|
---|
940 | filename: the name of Measurement set to be read.
|
---|
941 | outprefix: the prefix of output scantable name.
|
---|
942 | the names of output scantable will be
|
---|
943 | outprefix.antenna1, outprefix.antenna2, ....
|
---|
944 | If not specified, outprefix = filename is assumed.
|
---|
945 | overwrite If the file should be overwritten if it exists.
|
---|
946 | The default False is to return with warning
|
---|
947 | without writing the output. USE WITH CARE.
|
---|
948 |
|
---|
949 | """
|
---|
950 | # Import the table toolkit from CASA
|
---|
951 | try:
|
---|
952 | import casac
|
---|
953 | except ImportError:
|
---|
954 | if rcParams['verbose']:
|
---|
955 | #print "failed to load casa"
|
---|
956 | print_log()
|
---|
957 | asaplog.push("failed to load casa")
|
---|
958 | print_log('ERROR')
|
---|
959 | else: raise
|
---|
960 | return False
|
---|
961 | try:
|
---|
962 | tbtool = casac.homefinder.find_home_by_name('tableHome')
|
---|
963 | tb = tbtool.create()
|
---|
964 | tb2 = tbtool.create()
|
---|
965 | except:
|
---|
966 | if rcParams['verbose']:
|
---|
967 | #print "failed to load a table tool:\n", e
|
---|
968 | print_log()
|
---|
969 | asaplog.push("failed to load table tool")
|
---|
970 | print_log('ERROR')
|
---|
971 | else: raise
|
---|
972 | return False
|
---|
973 | # Check the input filename
|
---|
974 | if isinstance(filename, str):
|
---|
975 | import os.path
|
---|
976 | filename = os.path.expandvars(filename)
|
---|
977 | filename = os.path.expanduser(filename)
|
---|
978 | if not os.path.exists(filename):
|
---|
979 | s = "File '%s' not found." % (filename)
|
---|
980 | if rcParams['verbose']:
|
---|
981 | print_log()
|
---|
982 | asaplog.push(s)
|
---|
983 | print_log('ERROR')
|
---|
984 | return
|
---|
985 | raise IOError(s)
|
---|
986 | # check if input file is MS
|
---|
987 | if not os.path.isdir(filename) \
|
---|
988 | or not os.path.exists(filename+'/ANTENNA') \
|
---|
989 | or not os.path.exists(filename+'/table.f1'):
|
---|
990 | s = "File '%s' is not a Measurement set." % (filename)
|
---|
991 | if rcParams['verbose']:
|
---|
992 | print_log()
|
---|
993 | asaplog.push(s)
|
---|
994 | print_log('ERROR')
|
---|
995 | return
|
---|
996 | raise IOError(s)
|
---|
997 | else:
|
---|
998 | s = "The filename should be string. "
|
---|
999 | if rcParams['verbose']:
|
---|
1000 | print_log()
|
---|
1001 | asaplog.push(s)
|
---|
1002 | print_log('ERROR')
|
---|
1003 | return
|
---|
1004 | raise TypeError(s)
|
---|
1005 | # Check out put file name
|
---|
1006 | outname=''
|
---|
1007 | if len(outprefix) > 0: prefix=outprefix+'.'
|
---|
1008 | else:
|
---|
1009 | prefix=filename
|
---|
1010 | # Now do the actual splitting.
|
---|
1011 | outfiles=[]
|
---|
1012 | tmpms="temp_antsplit.ms"
|
---|
1013 | if os.path.exists(tmpms):
|
---|
1014 | ans=raw_input('Temporal file '+tmpms+' exists. Delete it and continue? [y/N]: ')
|
---|
1015 | if ans.upper() == 'Y':
|
---|
1016 | os.system('rm -rf '+tmpms)
|
---|
1017 | asaplog.push('The file '+tmpms+' deleted.')
|
---|
1018 | else:
|
---|
1019 | asaplog.push('Exit without splitting.')
|
---|
1020 | return
|
---|
1021 | tb.open(tablename=filename+'/ANTENNA',nomodify=True)
|
---|
1022 | nant=tb.nrows()
|
---|
1023 | antnames=tb.getcol('NAME',0,nant,1)
|
---|
1024 | antpos=tb.getcol('POSITION',0,nant,1).transpose()
|
---|
1025 | tb.close()
|
---|
1026 | tb.open(tablename=filename,nomodify=True)
|
---|
1027 | ant1=tb.getcol('ANTENNA1',0,-1,1)
|
---|
1028 | for antid in set(ant1):
|
---|
1029 | qstr="ANTENNA1 == "+str(antid)
|
---|
1030 | stab = tb.queryC(qstr)
|
---|
1031 | ctab = stab.copy(tmpms,deep=True)
|
---|
1032 | stab.close()
|
---|
1033 | ctab.close()
|
---|
1034 | scan=scantable(tmpms,average=False,getpt=True)
|
---|
1035 | outname=prefix+antnames[antid]+'.asap'
|
---|
1036 | scan.save(outname,format='ASAP',overwrite=overwrite)
|
---|
1037 | # Modify scantable header
|
---|
1038 | tb2.open(tablename=outname,nomodify=False)
|
---|
1039 | tb2.putkeyword(keyword='AntennaName',value=antnames[antid])
|
---|
1040 | tb2.putkeyword(keyword='AntennaPosition',value=antpos[antid])
|
---|
1041 | tb2.flush()
|
---|
1042 | tb2.close()
|
---|
1043 | del scan, ctab, stab
|
---|
1044 | outfiles.append(outname)
|
---|
1045 | tb.close()
|
---|
1046 | del tb, tb2
|
---|
1047 | os.system('rm -rf '+tmpms)
|
---|
1048 | return outfiles
|
---|
1049 |
|
---|
1050 | def _array2dOp( scan, value, mode="ADD", tsys=False ):
|
---|
1051 | """
|
---|
1052 | This function is workaround on the basic operation of scantable
|
---|
1053 | with 2 dimensional float list.
|
---|
1054 |
|
---|
1055 | scan: scantable operand
|
---|
1056 | value: float list operand
|
---|
1057 | mode: operation mode (ADD, SUB, MUL, DIV)
|
---|
1058 | tsys: if True, operate tsys as well
|
---|
1059 | """
|
---|
1060 | nrow = scan.nrow()
|
---|
1061 | s = None
|
---|
1062 | if len( value ) == 1:
|
---|
1063 | from asap._asap import stmath
|
---|
1064 | stm = stmath()
|
---|
1065 | s = scantable( stm._arrayop( scan.copy(), value[0], mode, tsys ) )
|
---|
1066 | del stm
|
---|
1067 | elif len( value ) != nrow:
|
---|
1068 | asaplog.push( 'len(value) must be 1 or conform to scan.nrow()' )
|
---|
1069 | print_log( 'ERROR' )
|
---|
1070 | else:
|
---|
1071 | from asap._asap import stmath
|
---|
1072 | stm = stmath()
|
---|
1073 | # insitu must be True
|
---|
1074 | stm._setinsitu( True )
|
---|
1075 | s = scan.copy()
|
---|
1076 | sel = selector()
|
---|
1077 | for irow in range( nrow ):
|
---|
1078 | sel.set_rows( irow )
|
---|
1079 | s.set_selection( sel )
|
---|
1080 | if len( value[irow] ) == 1:
|
---|
1081 | stm._unaryop( s, value[irow][0], mode, tsys )
|
---|
1082 | else:
|
---|
1083 | stm._arrayop( s, value[irow], mode, tsys, 'channel' )
|
---|
1084 | s.set_selection()
|
---|
1085 | sel.reset()
|
---|
1086 | del sel
|
---|
1087 | del stm
|
---|
1088 | return s
|
---|
1089 |
|
---|
1090 |
|
---|
1091 |
|
---|